doc:ollama document (#1512)

dbgpt/storage/vector_store/chroma_store.py

@@ -19,6 +19,7 @@
 
 CHROMA_COLLECTION_NAME = "langchain"
 
+
 @register_resource(
     _("Chroma Vector Store"),
     "chroma_vector_store",
@@ -152,7 +153,6 @@ def vector_name_exists(self) -> bool:
         files = list(filter(lambda f: f != "chroma.sqlite3", files))
         return len(files) > 0
 
-
     def load_document(self, chunks: List[Chunk]) -> List[str]:
         """Load document to vector store."""
         logger.info("ChromaStore load document")

dbgpt/storage/vector_store/pgvector_store.py

@@ -66,7 +66,7 @@ def __init__(self, vector_store_config: PGVectorConfig) -> None:
             embedding_function=self.embeddings,
             collection_name=self.collection_name,
             connection_string=self.connection_string,
-        )   # mypy: ignore
+        )  # mypy: ignore
 
     def similar_search(
         self, text: str, topk: int, filters: Optional[MetadataFilters] = None

docs/docs/installation/advanced_usage/ollama.md

@@ -0,0 +1,41 @@
+# ollama
+ollama is a model serving platform that allows you to deploy models in a few seconds. 
+It is a great tool.
+
+### Install ollama
+If your system is linux.
+```bash
+curl -fsSL https://ollama.com/install.sh | sh
+```
+other environments, please refer to the [official ollama website](https://ollama.com/).
+### Pull models.
+1. Pull LLM
+```bash
+ollama pull qwen:0.5b
+```
+2. Pull embedding model.
+```bash
+ollama pull nomic-embed-text
+```
+
+3. install ollama package.
+```bash
+pip install ollama
+```
+
+### Use ollama proxy model in DB-GPT `.env` file
+
+```bash
+LLM_MODEL=ollama_proxyllm
+PROXY_SERVER_URL=http://127.0.0.1:11434
+PROXYLLM_BACKEND="qwen:0.5b"
+PROXY_API_KEY=not_used
+EMBEDDING_MODEL=proxy_ollama
+proxy_ollama_proxy_server_url=http://127.0.0.1:11434
+proxy_ollama_proxy_backend="nomic-embed-text:latest"
+```
+
+### run dbgpt server
+```bash
+python dbgpt/app/dbgpt_server.py
+```

docs/sidebars.js

@@ -237,6 +237,10 @@ const sidebars = {
               type: 'doc',
               id: 'installation/advanced_usage/More_proxyllms',
             },
+            {
+              type: 'doc',
+              id: 'installation/advanced_usage/ollama',
+            },
             {
               type: 'doc',
               id: 'installation/advanced_usage/vLLM_inference',